Social Media: Pulse of the Planet?

In 2010, Hillary Clinton described social media as a new nervous system for our planet (1). So can the pulse of the planet be captured with social media? There are many who are skeptical not least because of the digital divide. “You mean the pulse of the Data Have’s? The pulse of the affluent?” These rhetorical questions are perfectly justified, which is why social media alone should not be the sole source of information that feeds into decision-making for policy purposes. But millions are joining the social media ecosystem everyday. So the selection bias is not increasing but decreasing. We may not be able to capture the pulse of the planet comprehensively and at a very high resolution yet, but the pulse of the majority world is certainly growing louder by the day.

This map of the world at night (based on 2011 data) reveals areas powered by electricity. Yes, Africa has far less electricity consumption. This is not misleading, it is an accurate proxy for industrial development (amongst other indexes). Does this data suffer from selection bias? Yes, the data is biased towards larger cities rather than the long tail. Does this render the data and map useless? Hardly. It all depends on what the question is.

What if our world was lit up by information instead of lightbulbs? The map above from TweetPing does just that. The website displays tweets in real-time as they’re posted across the world. Strictly speaking, the platform displays 10% of the ~340 million tweets posted each day (i.e., the “Decahose” rather than the “Firehose”). But the volume and velocity of the pulsing ten percent is already breathtaking.

One may think this picture depicts electricity use in Europe. Instead, this is a map of geo-located tweets (blue dots) and Flickr pictures (red dots). “White dots are locations that have been posted to both” (2). The number of active Twitter users grew an astounding 40% in 2012, making Twitter the fastest growing social network on the planet. Over 20% of the world’s internet population is now on Twitter (3). The Sightsmap below is a heat map based on the number of photographs submitted to Panoramio at different locations.

The map below depicts friendship ties on Facebook. This was generated using data when there were “only” 500 million users compared to today’s 1 billion+.

The following map does not depict electricity use in the US or the distribution of the population based on the most recent census data. Instead, this is a map of check-in’s on Foursquare. What makes this map so powerful is not only that it was generated using 500 million check-in’s but that “all those check-ins you see aren’t just single points—they’re links between all the other places people have been.”

TwitterBeat takes the (emotional) pulse of the planet by visualizing the Twitter Decahose in real-time using sentiment analysis. The crisis map in the YouTube video below comprises all tweets about Hurricane Sandy over time. “[Y]ou can see how the whole country lights up and how tweets don’t just move linearly up the coast as the storm progresses, capturing the advance impact of such a large storm and its peripheral effects across the country” (4).

These social media maps don’t only “work” at the country level or for Western industrialized states. Take the following map of Jakarta made almost exclusively from geo-tagged tweets. You can see the individual roads and arteries (nervous system). Granted, this map works so well because of the horrendous traffic but nevertheless a pattern emerges, one that is strongly correlated to the Jakarta’s road network. And unlike the map of the world at night, we can capture this pulse in real time and at a fraction of the cost.

Like any young nervous system, our social media system is still growing and evolving. But it is already adding value. The analysis of tweets predicts the flu better than the crunching of traditional data used by public health institutions, for example. And the analysis of tweets from Indonesia also revealed that Twitter data can be used to monitor food security in real-time.

The main problem I see about all this has much less to do with issues of selection bias and unrepresentative samples, etc. Far more problematic is the central-ization of this data and the fact that it is closed data. Yes, the above maps are public, but don’t be fooled, the underlying data is not. In their new study, “The Politics of Twitter Data,” Cornelius Puschmann and Jean Burgess argue that the “owners” of social media data are the platform providers, not the end users. Yes, access to Twitter.com and Twitter’s API is free but end users are limited to downloading just a few thousand tweets per day. (For comparative purposes, more than 20 million tweets were posted during Hurricane Sandy). Getting access to more data can cost hundreds of thousands of dollars. In other words, as Puschmann and Burgess note, “only corporate actors and regulators—who possess both the intellectual and financial resources to succeed in this race—can afford to participate,” which means “that the emerging data market will be shaped according to their interests.”

“Social Media: Pulse of the Planet?” Getting there, but only a few elite Doctors can take the full pulse in real-time.

7 responses to “Social Media: Pulse of the Planet?”

When I first saw TweetPing last week, I was also reminded of Senator Clinton’s nervous system quotes!
When you say that access to this type data can cost hundreds of thousands of dollars, have there already been cases of huge amounts of data being sold like this, and if so by and to whom?
Could national governments acquire/pay for access and make public the data during humanitarian/natural disasters in the interest of public safety?

In terms of your second question, yes, my colleague John Crowley at the Harvard Humanitarian Initiative (together with others) has been able to secure free access to satellite imagery from the US Government during times of disasters so that Digital Humanitarians can use this important data to support humanitarian operations. But I don’t know of many more examples. I’ve personally been calling for Big Data Philanthropy for disaster response: